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generating-sounds-with-ai

Audit Web Audio API code for sound synthesis best practices and output file:line findings.

3|Updated Apr 20, 2026
Search Tags:#typescript#code review#audiocontext#ui sounds#web audio api#procedural audio#sound synthesis
One-click install
npx skills add https://github.com/langgenius/due-date-hq-jwl --skill generating-sounds-with-ai-langgenius
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: generating-sounds-with-ai
Source: https://github.com/langgenius/due-date-hq-jwl/tree/main/.claude/skills/generating-sounds-with-ai
Command: npx skills add https://github.com/langgenius/due-date-hq-jwl --skill generating-sounds-with-ai-langgenius

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Procedural audio code written with the Web Audio API often contains subtle mistakes—leaked AudioContext instances, linear ramps that sound unnatural, exponential ramps targeting zero, or poorly tuned filter parameters—that produce glitches, harsh tones, or memory leaks. This Skill reviews that code against a defined rule set and reports each violation with an exact file and line number. ## Core Features & Use Cases - Rule-Based Auditing: Checks code against 13 rules across four categories: context management, envelope/decay, sound design, and parameter ranges. - Structured Findings: Outputs violations in file:line - [rule-id] description format plus a severity summary table. - Parameter Translation: Maps subjective feedback like "too harsh" or "too muffled" to concrete parameter changes such as filter frequency, Q value, or decay curve. - Use Case: A developer implementing UI click and confirmation sounds asks for a review of lib/sounds.ts and receives findings like lib/sounds.ts:23 - [envelope-exponential-decay] Using linearRampToValueAtTime instead of exponential. ## Quick Start Review the Web Audio API sound code in my project and report any violations of sound synthesis best practices with file and line numbers.

Frequently Asked Questions about generating-sounds-with-ai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review Web Audio API code for best practices?▼

Point the Skill at your audio source files and it checks them against 13 rules covering context management, envelopes, sound design, and parameters. Findings are reported in file:line format with rule IDs and a severity summary table.

What are common Web Audio API mistakes in UI sound design?▼

Common mistakes include creating a new AudioContext per sound, using linear ramps instead of exponential decay, targeting zero in exponential ramps, and using oscillators for clicks instead of filtered noise. Each produces glitches, unnatural decay, or tonal beeps instead of clean clicks.

Why does exponentialRampToValueAtTime fail when targeting zero?▼

Exponential ramps cannot mathematically reach zero, so the Web Audio API throws or behaves unexpectedly with a zero target. Use a small value like 0.001 instead, and set an initial value with setValueAtTime before ramping to avoid glitches.

Should I use an oscillator or noise buffer for click sounds?▼

Use a short filtered noise buffer for clicks and taps, typically 5-15ms through a bandpass filter at 3000-6000Hz. Oscillators produce tonal beeps suited to confirmations and pops, where pitch sweeps add character.

What are the limitations of automated audio code review?▼

The review is static and rule-based, so it checks code patterns rather than how the output actually sounds. Subjective qualities still require listening tests, though the parameter translation table maps feedback like "too harsh" to concrete adjustments.

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